AI in Network Market worth $21.52 billion by 2032
The report "AI in Network Market by Solution (Network Management, Network Optimization, Network Security, Network Automation, Network Orchestration, Network Planning & Design) - Global Forecast to 2032", The AI in network market is projected to grow from USD 8.38 billion in 2026 and to reach USD 21.52 billion by 2032, at a CAGR of 17.0% during 2026–2032. Growing network complexity, rising data volumes, and increasing demand for automation and real-time visibility are accelerating AI adoption in network solutions. Enterprises and service providers are increasingly investing in AI-powered network management, predictive analytics, intelligent monitoring, and automation to improve network performance, reduce downtime, and optimize resource utilization. The expansion of cloud, 5G, and edge computing further increases the need for intelligent network infrastructure that can analyze large volumes of data and enable faster decision-making.
The growing deployment of AI-enabled networking technologies enables continuous analysis of network traffic, performance, anomalies, and infrastructure health. These solutions support predictive maintenance, automated fault detection, traffic optimization, capacity planning, and faster incident resolution. AI-driven decision-making helps reduce operational costs and downtime while improving network security and user experience. As organizations prioritize network automation, resilience, and intelligent infrastructure management, AI adoption in networks is expected to expand across developed and emerging economies.
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“By solution, the AI-driven network management segment is expected to hold the largest market share during the forecast period.”
The AI-driven network management segment is expected to account for the largest share of the global AI in network market, driven by growing network complexity, rising data volumes, and the need for automated, real-time network operations. Enterprises and communication service providers are increasingly adopting AI-driven solutions for network monitoring, configuration, optimization, fault detection, and performance management. The growing adoption of 5G, edge computing, cloud, hybrid-cloud, IoT, and software-defined networking is further driving demand for intelligent network management. These solutions leverage machine learning, predictive analytics, generative AI, and automation to detect anomalies, predict failures, optimize resources, and accelerate incident resolution, helping organizations reduce operational costs, minimize downtime, and improve network performance. Integrating AI with network observability, digital twins, intent-based networking, and closed-loop automation is further enabling self-optimizing networks. As digital transformation accelerates, AI-driven network management is becoming critical for scalable, resilient, and autonomous network operations.
“By service, the managed services segment is expected to witness a higher growth rate during the forecast period.”
The managed services segment is expected to grow rapidly as enterprises increasingly outsource AI-driven network monitoring, optimization, and maintenance to improve performance and reduce operational complexity. The growing complexity of hybrid, multi-cloud, and 5G networks, along with rising network traffic, is driving demand for real-time monitoring, predictive maintenance, automated troubleshooting, and performance optimization.
Managed services also support AI adoption by providing AI-powered analytics and automation without significant in-house investments. The increasing deployment of AIOps, edge computing, software-defined networking, and cloud-based network environments is enabling proactive fault detection, enhanced security, and improved network resilience, further driving segment growth.
“Asia Pacific is expected to register the highest growth rate during the forecast period.”
Asia Pacific is projected to register the highest growth rate in the AI in network market during the forecast period, driven by rapid 5G deployment, increasing network complexity, rising investments in cloud and edge infrastructure, and strong adoption of AI-driven network optimization across countries such as China, Japan, South Korea, India, and Singapore. Telecom operators and enterprises are increasingly deploying AI for network optimization, predictive maintenance, traffic management, network security, and autonomous operations to improve network performance, reduce operational costs, and enhance user experience. The region’s transition toward AI-native and 6G networks is further accelerating market growth, with operators focusing on software-defined architectures, distributed AI, and AI-enabled RAN capabilities. A notable recent development is the March 2026 collaboration between NTT DOCOMO and SK Telecom, which produced a joint white paper outlining the technical requirements and enabling technologies for evolving vRAN into AI-RAN, reinforcing Asia Pacific’s leadership in AI-native network development.
Market Players
The major vendors covered in the AI in network market are Cisco (US), HPE (US), Nokia (Finland), Ericsson (Sweden), Huawei (China), Arista Networks (US), NVIDIA (US), Extreme Networks (US), Broadcom (US), IBM (US), Fujitsu (Japan), Dell Technologies (US), Ciena (US), NEC (Japan), Forward Networks (US), BlueCat Networks (Canada), A10 Networks (US), ScienceLogic (US), Versa Networks (US), Dynatrace (US), Infoblox (US), EfficientIP (France), Riverbed (US), NETSCOUT (US), SolarWinds (US), NetBrain (US), ManageEngine (US), VIAVI Solutions (US), Selector (US), Aviz Networks (US), Nile (US), NetBox Labs (US), Celona (US), Shabodi (Canada), and A5G Networks (US).
These players have adopted various growth strategies, such as partnerships, agreements, collaborations, new product launches, enhancements, and acquisitions, to expand their footprint in the AI in network market.
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